Leveraging AI and Data Spaces to Revolutionise Agrobusiness
The agricultural and food supply chain (AFSC) boasts numerous implementations of data-based decision-support systems across both scientific and industrial sectors. However, most of these systems operate in isolation (silos). They typically involve a single stakeholder, or if multiple parties are involved, data sharing occurs on an ad-hoc basis.
The EBDVF session shall highlight how the generation of AI models to solve Agrifood Supply Chain (AFSC) issues using the resources and the data shared through data spaces. It will review the AI trends (such as the application of Generative AI) and the current state of data spaces to solve AFSC problems and:
- Highlight the need for the Data Spaces to foster the paradigm shift through the AFSC.
- Provide practical examples of the application of Data Spaces as articulators of Big Data and AI projects.
- Create a debate to seed new ideas and projects.
This session examines how Data Spaces can unlock the full potential of data collected throughout a sustainable agro-industrial chain. We will start by exploring how a more holistic and sustainable data management approach enhances decision-making and fosters new synergies, ultimately paving the way for a greener future. Next, we will look at a practical example: the Data Space being developed at ZeroW, as it highlights the secure and reliable sharing of data among actors at different points in the supply chain. The final talk will cover the use of Geospatial Large Language Models (GeoLLM) in agriculture, showcasing how these models can enhance decision-making by providing data-driven insights on crop yields, health and resource allocation.
The session will conclude with a Q&A segment, allowing presenters and attendees to engage in meaningful dialogue.
